The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

A total of 72 individuals of genus Pristina were sorted from aquatic plant, Ceratophyllum demersum L., and filamentous algae collected from three sites on Tigris River at Baghdad including: Al-Sarafiya area (S1), Al- Jadiriyah area (S2), and Al- Za´afaraniya area (S3). Four species were identified including P. longiseta, P. aequiseta, P. proboscidea and P. foreli, with percentags of 51.7 , 36.4, 1.1, and 10.5 % respectively. The first two species found in all sites , while , P. proboscidea found only in S1 and P. foreli only in S2.

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

In this study, the amounts of activity concentrations of naturally occurring in 10 soil samples of the Tigris river and surrounding areas collected from deferent city of Baghdad have been investigated. Tigris river is an important water source for irrigation and drinking in Iraq. This study was done during 2018 in Protection Center of the Iraqi Ministry of Health and Environment using a high purity germanium detector. The resolution of (HPGe) at 2keV and 30% efficiency. The results of soil sample obtained showed that the effective activity concentration of 40K are ranged from 181.4 Bq/kg in sample S6 to 286.4 Bq/kg in S7. For Raeq values are ranged from 6 Bq/m3 in sample S5 to 17 Bq/m3 in sample S3. The obtained data revealed that the me

The physical and chemical parameters of Tigris River water in AL- Kut City have been studied. Three stations have been chosen. . The sampling of study was made monthly and for six months from September 2014 until February 2015.The result of turbidity values showed height mean in summer 84 NTU, The decrease of turbidity was one of the positive results to the effect of AL-Kut Dam on the Tigris River after the Dam and on the total suspended solids. The electrical conductivity was 1340 µs/cm in winter that may be due to the existence of the polluted elements. The river water was fresh (0.48‰ semiebrachish) with a good aerated water and the height of the dissolved oxygen mean value has been noticed 13.1mg/L at many times. Over satura

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

   In this paper we give definitions, properties and examples of the notion of  type Ntopological space. Throughout this paper  N is a finite positive  number, N 2. The task of this paper is to study and investigate some properties of such spaces with the existence of a relation between this space and artificial Neural Networks (NN'S), that is we applied the definition of this space in computer field and specially in parallel processing

ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, auto